The present invention relates generally to wireless systems and, more particularly, to interference management for distributed antenna systems.
In a distributed antenna system (DAS), multiple distributed antennae are set up in a geographical region and are connected via fiber to a centralized Base Station (CBS) which manages these antennae. The antennae are grouped into clusters which serve users (UEs).
Frequency partitioning is a well-known concept used to eliminate inter-cell interference in cellular networks. FIG. 1 shows an example of a cellular network where different sectors of a cell are assigned different frequency bands (d1, d2, d3) so that co-channel interference is minimized at adjacent sectors of different cells. For example, in cell C6, the sector with frequency band “d1” does not have any neighboring sectors operating at the same frequency band. Thus, co-channel interference from neighboring cells is completely eliminated and only weak interference is received from far away cells.
Another well-known concept pertinent to interference management is downlink interference alignment. Interference alignment (IA) is a Physical layer technique used to minimize the impact of co-channel interference. Different from frequency partitioning, IA attempts to align the transmit directions of all interferers so that all the interference at the receiver is aligned in the same direction (or subspace). Interference alignment can be done in several dimensions including frequency, time, and space (e.g., antennas). FIG. 2 shows a schematic diagram with three base stations performing interference alignment for downlink transmission.
In Changho Suh et al., “Downlink Interference Alignment,” http://arxiv.org/abs/1003.3707, 2010, the authors present a downlink IA technique where space dimension is used to align interference. FIG. 3 (FIG. 2 in the original Suh et al. paper) shows the illustration in Suh et al. of a two-cell network with BS α and β each employing a fixed precoder P. Each cell has two users. The matrix Hαk indicates the channel matrix between BS α and the kth user associated with it. The matrix Gβk indicates the interference channel matrix between BS β and the kth user associated with BS α. In order to align the interference, the kth user computes the null vector, uαk, corresponding to the effective interference channel matrix GβkP such that uαkGβkP=0. Next, the user feeds back the effective channel matrix, uαkHαkP, to BS α. These steps are repeated by all users for the two cells as shown in FIG. 3. Next, each BS computes the ZF-precoding matrices for the overall effective channel matrix (e.g., the effective channel matrix for BS α is Hα=[uα1Hα1P; uα2Hα2P]). The ZF-precoding matrices can be computed using the technique disclosed in Q. H Spencer, A. L. Swindlehurst & M. Haardt, “Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels,” IEEE Transactions on Signal Processing, pp. 461-471, February 2004. The entire disclosures of these two references are incorporated herein by reference.